dplyr-ggplot2-shiny-barplot.R

library(shiny)
library(dplyr)
library(ggplot2)
library(bslib)

set.seed(42)
data <- data.frame(
  category = c("A", "B", "C", "D", "E"),
  value = sample(10:100, 5)
)

ui <- page_fluid(
  h1("dplyr and ggplot2 Bar Chart in Shiny"),
  card(
    card_header("Sample Bar Chart"),
    plotOutput("bar_chart", height = "400px")
  ),
  card(
    card_header("Data Table"),
    dataTableOutput("data_table")
  )
)

server <- function(input, output, session) {
  output$bar_chart <- renderPlot({
    plot_data <- data %>%
      mutate(category = factor(category, levels = category))  
    my_colors <- c("#1f77b4", "#ff7f0e", "#2ca02c", "#d62728", "#9467bd")
    ggplot(plot_data, aes(x = category, y = value, fill = category)) +
      geom_bar(stat = "identity", width = 0.7) +      
      geom_text(aes(label = value), vjust = -0.5, size = 4) +      
      labs(
        title = "Bar Chart using dplyr and ggplot2",
        x = "Category",
        y = "Value"
      ) +      
      scale_fill_manual(values = my_colors) +  
      theme_minimal() +
      theme(
        plot.title = element_text(size = 16, face = "bold"),
        axis.title = element_text(size = 12),
        legend.position = "none",
        panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank()
      )
  })
  output$data_table <- renderDataTable({
    data
  })
}

shinyApp(ui, server)

polars-altair-shiny-barplot.py

from shiny import App, ui, render
import polars as pl
import altair as alt
import numpy as np
import json

alt.renderers.enable('default')
alt.data_transformers.disable_max_rows()

np.random.seed(42)
data = pl.DataFrame({
    "category": ["A", "B", "C", "D", "E"],
    "value": np.random.randint(10, 100, 5)
})

app_ui = ui.page_fluid(
    ui.h1("Polars and Altair Bar Chart in Shiny"),
    ui.card(
        ui.card_header("Sample Bar Chart"),
        ui.output_ui("bar_chart"),
    ),
    ui.card(
        ui.card_header("Data Table"),
        ui.output_data_frame("data_table")
    ),
    # Include required Vega-Lite libraries directly in the page
    ui.tags.script(src="https://cdn.jsdelivr.net/npm/vega@5"),
    ui.tags.script(src="https://cdn.jsdelivr.net/npm/vega-lite@5"),
    ui.tags.script(src="https://cdn.jsdelivr.net/npm/vega-embed@6")
)

def server(input, output, session):
    @render.ui
    def bar_chart():
        chart = alt.Chart(alt.Data(values=data.to_dicts())).mark_bar().encode(
            x=alt.X('category:N', title='Category'),
            y=alt.Y('value:Q', title='Value'),
            color=alt.Color('category:N', legend=None)
        ).properties(
            width=400,
            height=300,
            title='Bar Chart using Polars and Altair'
        )
        chart_spec = json.loads(chart.to_json())
        div_id = "vis-chart"
        html = f"""
        <div id="{div_id}" style="width: 100%; max-width: 800px;"></div>
        <script type="text/javascript">
            var spec = {json.dumps(chart_spec)};
            vegaEmbed('#{div_id}', spec, {{renderer: 'svg'}})
              .then(function(result) {{
                console.log('Chart rendered successfully');
              }})
              .catch(console.error);
        </script>
        """
        return ui.HTML(html)
    
    @render.data_frame
    def data_table():
        return data

app = App(app_ui, server)